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parametric estimation中文是什么意思

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  • For the negative and invalid output data exists universally in reality , the method which adopts non - parametric estimation method to filtrate the data is put forward and illustrated with an example , the characteristics of the method is analyzed at last
    4 .针对现实生活中普遍存在负的和无效产出数据情形,文中提出了采用非参数模型进行过滤数据的方法,给出了具体算例,并对这种算法进行了分析。
  • In this essay , firstly the author analyzes the predictability of time series from china ' s stock exchange using three kinds of methods : arma model , neural network model and non - parametric estimation and gives evaluation on their performances while at the same time puts forward some conclusions deserving attention from both stock exchange supervising department and stock traders . secondly , the author examines the assumptions closely on which the above - said methods base and gives a detailed discussion on them , especially using garch model to test quantitatively the stability of china ' s stock exchange , afterwards drawing the conclusion that it is hard to make accurate prediction of price or return rate of china ' s stocks for none of the assumptions fully holds ground . thirdly , taking account of the difference between chinese stock traders as a whole and that of developed countries , the author gives a thorough analysis on the complexity and volatility of its ( traders " ) reaction to information and points out that the intrinsic heterogeneous and volatile reaction to information is an important reason for the almost unpredictability of the price or return rate in china ' s stock exchange
    本文首先采用arma模型、非参数模型以及神经网络模型对我国股市时间序列进行研究,对三种方法在分析我国股市时间序列的表现进行评价,并得出了一些对监管部门以及股票交易者有借鉴意义的结论;其次作者对三种模型分析我国股市时间序列的前提进行了讨论,特别是利用garch模型对我国股市的系统稳定性进行了量化检验,得出了前提难以满足导致准确预测我国股市价格或收益率困难的结论;第三,考虑到中国股市股票交易者群体与发达国家股市股票交易者群体之间的差异,作者借用行为金融学的理论成果对我国股票交易者对信息反应的复杂性和易变性进行了详细分析,指出股票交易者对信息反应的异质性和易变性是造成难以准确预测我国股市的一个重要原因,考虑到我国股市以散户为主导的特性将长期存在,因此将行为金融学的研究结论纳入对我国股市时间序列的量化研究具有重要的意义;最后,作者从唯理预测与唯象预测之间差异的角度出发,指出了唯象预测的缺点并对我国股市时间序列的研究方向进行了展望。
  • A new robust adaptive scheme which are used for tracking of this robot with parametric and bounded external uncertainties is proposed in this thesis . the controller is consist of a controller which is proposed by slotine1 ' 1 and nonlinear continued feedback compensation part . by estimating the unknown physical parameters of robot on - line , it can eliminate the effects result by parameters and external disturbances and guarantee gas and uniform boundedness of parametric estimation . the only information required in setting up the strategy is the output states of jionts , while the inversion of the inertia matrix or estimation the bound of the inertia matrix and measure the jionts accelerations are not needed . it is shown by simulations that the proposed control scheme has quicker convergence velocity and better control precision than paper [ 1 ] and control schemes at present
    针对该模型具有参数及有界外部扰动不确定性时提出了一种新的鲁棒自适应控制策略,控制器由基于slotine的控制器和非线性连续反馈补偿控制器构成。通过在线估计机器人的未知物理参数,有效的消除了由参数及外部扰动所引起的不确定性影响,保证系统达到渐近稳定和参数估计一致有界。与现存的许多控制方法相比,该控制策略不需求解惯性矩阵的逆或估计惯性矩阵的界,不需测量关节加速度,而唯一需要了解的只是系统输出的位置及速度状态。
  • In addition , adopting genetic algorithm to search the parameters of parametric estimation method is put forward . for the function form assumption of parametric estimation method is subjective , adopting different function form to construct production frontier is analyzed , the concepts such as tle ( total loss of efficiency ) and ale ( average loss of efficiency ) etc . are put forward and the empirical research is done
    2 .文中提出了采用遗传算法寻求生产前沿面参数的方法,针对参数生产前沿面函数形式假设偏主观性的特点,文中对不同生产函数形式假设构造参数生产前沿面的优劣进行了研究,定义了总失效率、平均失效率等概念。
  • 3 . on the base of non - parametric estimation method , the efficiency measurement is researched . with an example of electric power industry , pure technique - efficiency , size - efficiency , input disposition - degree , input component - efficiency and the input combination - efficiency are analyzed in this dissertation , and the calculating results are optimized and analyzed in the end
    以电力工业为例,具体分析了不同电力公司基于投入的投入规模效率、投入要素可处置度、投入纯技术效率和投入要素组合效率,并在最后对计算结果进行了优化和分析。
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Last modified time:Mon, 11 Aug 2025 00:29:56 GMT

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